/*
 * Licensed to the Apache Software Foundation (ASF) under one or more
 * contributor license agreements.  See the NOTICE file distributed with
 * this work for additional information regarding copyright ownership.
 * The ASF licenses this file to You under the Apache License, Version 2.0
 * (the "License"); you may not use this file except in compliance with
 * the License.  You may obtain a copy of the License at
 *
 *    http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

package com.zhaohg.spark.examples.streaming;

import org.apache.spark.SparkConf;
import org.apache.spark.api.java.JavaPairRDD;
import org.apache.spark.api.java.Optional;
import org.apache.spark.api.java.StorageLevels;
import org.apache.spark.api.java.function.Function3;
import org.apache.spark.api.java.function.PairFunction;
import org.apache.spark.streaming.Durations;
import org.apache.spark.streaming.State;
import org.apache.spark.streaming.StateSpec;
import org.apache.spark.streaming.api.java.JavaDStream;
import org.apache.spark.streaming.api.java.JavaMapWithStateDStream;
import org.apache.spark.streaming.api.java.JavaPairDStream;
import org.apache.spark.streaming.api.java.JavaReceiverInputDStream;
import org.apache.spark.streaming.api.java.JavaStreamingContext;
import scala.Tuple2;

import java.util.Arrays;
import java.util.List;
import java.util.regex.Pattern;

/**
 * Counts words cumulatively in UTF8 encoded, '\n' delimited text received from the network every
 * second starting with initial value of word count.
 * Usage: JavaStatefulNetworkWordCount <hostname> <port>
 * <hostname> and <port> describe the TCP server that Spark Streaming would connect to receive
 * data.
 * <p>
 * To run this on your local machine, you need to first run a Netcat server
 * `$ nc -lk 9999`
 * and then run the example
 * `$ bin/run-example
 * org.apache.spark.examples.streaming.JavaStatefulNetworkWordCount localhost 9999`
 */
public class JavaStatefulNetworkWordCount {
    private static final Pattern SPACE = Pattern.compile(" ");

    public static void main(String[] args) throws Exception {
        if (args.length < 2) {
            System.err.println("Usage: JavaStatefulNetworkWordCount <hostname> <port>");
            System.exit(1);
        }

        StreamingExamples.setStreamingLogLevels();

        // Create the context with a 1 second batch size
        SparkConf sparkConf = new SparkConf().setAppName("JavaStatefulNetworkWordCount");
        JavaStreamingContext ssc = new JavaStreamingContext(sparkConf, Durations.seconds(1));
        ssc.checkpoint(".");

        // Initial state RDD input to mapWithState
        @SuppressWarnings("unchecked")
        List<Tuple2<String, Integer>> tuples = Arrays.asList(new Tuple2<>("hello", 1), new Tuple2<>("world", 1));
        JavaPairRDD<String, Integer> initialRDD = ssc.sparkContext().parallelizePairs(tuples);

        JavaReceiverInputDStream<String> lines = ssc.socketTextStream(args[0], Integer.parseInt(args[1]), StorageLevels.MEMORY_AND_DISK_SER_2);

        JavaDStream<String> words = lines.flatMap(x -> Arrays.asList(SPACE.split(x)).iterator());

        JavaPairDStream<String, Integer> wordsDstream = words.mapToPair(
                (PairFunction<String, String, Integer>) s -> new Tuple2<>(s, 1));

        // Update the cumulative count function
        Function3<String, Optional<Integer>, State<Integer>, Tuple2<String, Integer>> mappingFunc =
                (word, one, state) -> {
                    int sum = one.orElse(0) + (state.exists() ? state.get() : 0);
                    Tuple2<String, Integer> output = new Tuple2<>(word, sum);
                    state.update(sum);
                    return output;
                };

        // DStream made of get cumulative counts that get updated in every batch
        JavaMapWithStateDStream<String, Integer, Integer, Tuple2<String, Integer>> stateDstream =
                wordsDstream.mapWithState(StateSpec.function(mappingFunc).initialState(initialRDD));

        stateDstream.print();
        ssc.start();
        ssc.awaitTermination();
    }
}
